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Cutting out the middleman: Separating attributional biases from memory deficits

Published online by Cambridge University Press:  03 January 2020

Wei-Chun Wang*
Affiliation:
Department of Psychology, University of California, Berkeley, CA94720-1650. wcwang@berkeley.edu

Abstract

Bastin and colleagues present an integrative model of how recollection- and familiarity-based memories are represented in the brain. While they emphasize the role of attribution mechanisms in shaping memory retrieval, prior work examining implicit memory suggests that memory deficits may be better understood by separating attributional biases from the underlying memory traces.

Information

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2020